torch-mlir/test/RefBackend/restricted-canonicalize.mlir

35 lines
1.3 KiB
MLIR

// RUN: npcomp-opt -restricted-canonicalize=included-dialects=std <%s -split-input-file \
// RUN: | FileCheck %s --check-prefix=STDONLY --dump-input=fail
// RUN: npcomp-opt -restricted-canonicalize=included-dialects=shape <%s -split-input-file \
// RUN: | FileCheck %s --check-prefix=SHAPEONLY --dump-input=fail
// RUN: npcomp-opt -restricted-canonicalize=included-dialects=std,shape <%s -split-input-file \
// RUN: | FileCheck %s --check-prefix=STDANDSHAPE --dump-input=fail
// RUN: not --crash npcomp-opt -restricted-canonicalize=included-dialects=notreal2,notreal1 <%s -split-input-file 2>&1 \
// RUN: | FileCheck %s --check-prefix=ERROR --dump-input=fail
// ERROR: restricted-canonicalize: unknown dialects: notreal1, notreal2
// STDONLY-LABEL: func @mixed_dialects
// SHAPEONLY-LABEL: func @mixed_dialects
// STDANDSHAPE-LABEL: func @mixed_dialects
func @mixed_dialects(%arg0: i32) -> i32 {
// Do we canonicalize away the shape.assuming?
// STDONLY: shape.assuming
// SHAPEOONLY-NOT: shape.assuming
// STDANDSHAPE-NOT: shape.assuming
%w = shape.const_witness true
%0 = shape.assuming %w -> (i32) {
%c0 = constant 0 : i32
shape.assuming_yield %c0 : i32
}
// Do we canonicalize away the std.br?
// STDONLY-NOT: br
// SHAPEOONLY: br
// STDANDSHAPE-NOT: br
br ^bb1
^bb1:
return %0 : i32
}